RecruitingNCT06002711
Multi-Dimensional MRI Spatial Heterogeneity Analysis for Predicting Key Genes and Prognosis of High-Grade Gliomas: A Multi-Center Study
Sponsor
RenJi Hospital
Enrollment
500 participants
Start Date
Sep 1, 2023
Study Type
OBSERVATIONAL
Conditions
Summary
1. To retrospectively explore the feasibility of multi-dimensional heterogeneity imaging features of MRI in predicting the status of key gene mutations in high-grade gliomas; 2. To prospectively explore the correlation between multi-dimensional heterogeneous MRI image features and prognosis of high-grade glioma patients.
Eligibility
Min Age: 18 YearsMax Age: 70 Years
Inclusion Criteria14
- Retrospective Study:
- Participants aged 18 to 70 years, of any gender.
- Confirmed postoperative pathology of adult diffuse glioma (WHO Grade III-IV).
- Standard MR contrast-enhanced imaging performed within 10 days before surgery.
- No history of prior radiotherapy or chemotherapy before surgery.
- Absence of concurrent significant comorbidities or other tumors.
- Presence of molecular testing results (including IDH, MGMT, 1p19q, TERT, CDKN2A/B, BRAF).
- Availability of comprehensive clinical and follow-up data.
- Prospective Study:
- Participants aged 18 to 70 years, of any gender.
- Clinically suspected to have high-grade gliomas preoperatively, with final pathology confirming high-grade gliomas.
- Stable vital signs and capable of cooperating for a 40-minute MR scan.
- Absence of significant underlying medical conditions or history of other tumors.
- Documentation of informed consent through a signed consent form.
Exclusion Criteria7
- Retrospective Study:
- MRI images with artifacts or presence of intratumoral hemorrhage.
- Incomplete clinical data available.
- Prospective Study:
- Individuals with claustrophobia or other reasons unable to undergo MRI scans.
- History of allergic reactions to MRI contrast agents.
- Inappropriate for prolonged MRI scans due to other reasons.
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Interventions
DIAGNOSTIC_TESTMR scanning; Clinical data collection
Multi-dimensional spatial heterogeneity analysis of MRI
Locations(2)
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NCT06002711
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